A unique thermal system coupled with thermal energy and carbon capturing and storage options
Bibliographic record
Abstract
In this work, a Municipal Solid Waste (MSW) and solar thermal driven trigeneration system for production, space heating, and freshwater production is developed and thermodynamically assessed. The novelty of this work includes the use of MSW composition listed for Ontario, as fuel feed to an air-Brayton cycle, as well as coupling a heat pump to it through water conduits, to carry out thermal desalination and space heating applications. Related calculations are carried out using corresponding mass, energy, entropy, and exergy balance equations of key system components, and Engineering Equation Solver (EES). The integrated heat pump utilizes R134a refrigerant and is driven by solar thermal collectors during periods when sunlight is available, and through sensible thermal energy storage otherwise. Under nominal operating conditions, an irradiance of 800 W/m 2 is considered, and the energy and exergy efficiencies of 37.43 % and 24.55 %, are achieved, respectively. Moreover, a coefficient of performance of 2.72 is obtained for the same operating conditions. For more location specific calculations, the solar profile for the Durham region in Ontario, Canada, is used and values are obtained as yearly averages for irradiance. This results in a variation of energy and exergy efficiencies across a diurnal operation, where they range between 52.56 % to 43.98 % and 35.67 % to 29.27 %, respectively. The thermal energy storage charging capacity ranges between 2,624 kWh to 12,985 kWh during the day, and results in a uniform discharge capacity of 6,297 kWh for periods of no sunlight where energy and exergy efficiencies are obtained to be 49.43 % and 33.3 %, respectively. The variation of the reference temperature is also considered where the exergy efficiency decreases from 24.55 % to 23.38 %, as the reference temperature increases from 296.15 K to 340 K for 800 W/m 2 irradiance. Finally, corresponding exergy destruction calculations are carried out to determine potential room for improvement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".